Abstract

There is a need for new methods to identify lead structures in drug design. New potential lead structures should be identified by comparing not yet synthesized substances to structures with known activity. Similarities of known and unknown structures should be determined by comparing physicochemical and structural properties. Substances of unknown activity are made available by voluminous substance databases. Common approaches to similarity concentrated on the identification of pharmacophor models within the three dimensional structure of molecules. This project used a new approach by comparing the molecular surfaces that play an important role in receptor binding. It also takes into account surface properties like the charge distribution. The method is based on Kohonen maps. It maps molecular surfaces onto spherical maps that, due to their rotational invariant properties, can easily be compared with each other. The substance databases usually do not include three dimensional structural data. Therefore, a method for conformational searching was developed as a foundation for the surface comparisons. The method employs Genetic Algorithms and generates a single optimal structure as well as a set of plausible structures. Furthermore, a method was developed that uses physicochemical properties, derived from two dimensional structural data, for similarity analysis. A Kohonen map, trained with property vectors of all structures in a substance database, delivers a set of potential lead structures, when queried with a structure with known activity. (orig.)SIGLEAvailable from TIB Hannover: F97B2185+a / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekBundesministerium fuer Bildung, Wissenschaft, Forschung und Technologie, Bonn (Germany)DEGerman